The field of the disclosure relates generally to inspection of manufactured components and systems, and more specifically, to systems and methods for automated manufacturing anomaly location and classification.
There is currently no automated method for collection of both location data and visual classification data for manufacturing anomalies or aircraft on ground (AOG) inconsistencies that occur during aircraft use. Typically, this data is obtained by simple visual inspection. In some cases, the visually obtained data is used immediately to repair the anomaly. However, the observation may not be recorded for long-term tracking or statistical process control. In addition, when the data is collected visually, the exact location of the anomaly is approximated by the human inspector. Collecting sufficient data to accurately characterize manufacturing anomalies and/or inconsistencies with respect to an object during manufacturing processes is expensive and time consuming.
Moreover, users would have to accurately measure and record the location, type, severity and disposition of anomalies to generate any meaningful data. In the typical manufacturing process, however, the users simply repair the anomaly manually with no data collected, for example, for location, severity and type. When data is managed to be collected, it is typically entered manually into paper forms or logbooks. Multiple users keep multiple logbooks or fill multiple forms, one for each anomaly. There is no process in place for accumulating the form/logbook data.
However, if the data were collected it would go a long way in improving existing processes by determining trends in anomaly occurrence locations, types or other common factors. In certain instances, automated repair of these manufacturing anomalies might be enabled.